Quantification of shoulder muscle intramuscular fatty infiltration on T1-weighted MRI: a viable alternative to the Goutallier classification system View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Derik L. Davis, Thomas Kesler, Mohit N. Gilotra, Ranyah Almardawi, Syed A. Hasan, Rao P. Gullapalli, Jiachen Zhuo

ABSTRACT

BACKGROUND: Quantification of rotator cuff intramuscular fatty infiltration is important for clinical decision-making in patients with rotator cuff tear. The semi-quantitative Goutallier classification system is the most commonly used method, but has limited reliability. Therefore, we sought to test a freely available fuzzy C-means segmentation software program for reliability of the quantification of shoulder intramuscular fatty infiltration on T1-weighted MR images and for correlation with fat fraction by six-point Dixon MRI. MATERIALS AND METHODS: We performed a prospective cross-sectional study to measure visible intramuscular fat area percentage on oblique sagittal T1 MR images by fuzzy C-means segmentation and fat fraction maps by six-point Dixon MRI for 42 shoulder muscles. Intra- and inter-observer reliability were determined. Correlative analysis for fuzzy C-means and six-point Dixon intramuscular fatty infiltration measures was also performed. RESULTS: We found that inter-observer reliability for the quantification of visible intramuscular fat area percentage by fuzzy C-means segmentation and fat fraction by six-point Dixon MRI was 0.947 and 0.951 respectively. The intra-observer reliability for the quantification of visible intramuscular fat area percentage by fuzzy C-means segmentation and fat fraction by six-point Dixon MRI was 0.871 and 0.979 respectively. We found a strong correlation between fuzzy C-means segmentation and six-point Dixon techniques; r = 0.850, p < 0.001 by individual muscle; and r = 0.977, p < 0.002 by study subject. CONCLUSION: Quantification of intramuscular fatty infiltration by fuzzy C-means segmentation on T1-weighted sequences demonstrates excellent reliability and strong correlation with fat fraction by six-point Dixon MRI. Quantitative fuzzy C-means segmentation is a viable alternative to the semi-quantitative Goutallier classification system. More... »

PAGES

535-541

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00256-018-3057-7

DOI

http://dx.doi.org/10.1007/s00256-018-3057-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106903958

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30203182


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